Ph.D. scholarships in Computational SPS

The Department of Social and Political Sciences (SPS) establishes 1 scholarship in Computational Political Science and 2 scholarships in Computational Social Science, thanks to its Departments of Excellence award and the National Research Council.

Luigi Curini, Fabio Franchino, Alessia Damonte, and Flaminio Squazzoni are inviting applications from qualified and highly motivated students interested in improving their quantitative and programming skills to study relevant socio-economic, organizational, and political issues. The ideal methodological focus is on computational techniques such as machine learning, complex network analysis, agent-based modeling, text analytics, and culture analytics, among others.

The selected candidates will benefit from an exciting, free, interdisciplinary learning environment with extensive networking opportunities. The SPS Department currently hosts 5 ERC-funded projects and many H2020 projects and is highly international. The Computational Ph.D. candidates will work within the Computational Models and Designs Hub and be offered a comprehensive set of methodological seminars tailored to their specific interests, along with access to the core training of the NASP Ph.D. programs in Political Studies and Economic Sociology and Labour Studies.

You can find the full call for applications for the scholarship in Computational Political Science here. Please note the hard deadline for applications is May, 5 h.02:00 pm CEST (GMT+2).

The call for applications to the two scholarships in Computational Social Science will be published in June 2023.

The students will start their first year in October 2023. Any students applying must graduate before the beginning of the program.

For any questions and additional information regarding the Ph.D. project, the structure of the program, and the amount and years of the scholarships, please contact Luigi Curini for the scholarship in Computational Political Science or Flaminio Squazzoni for the two scholarships in Computational Social Science.